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Brian R. Jackson, M.D.

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Specialties

Languages

Specialties

Pathology, Clinical

Bio

Brian R. Jackson, MD, MS Vice President Chief Medical Informatics Officer As vice president and chief medical informatics officer, Dr. Jackson directs the Informatics Department at ARUP, including ARUP Consult®, decision support, product management, informatics software development, and ATOP® consulting. He is also the medical director for Referral Testing and an associate professor of pathology at the University of Utah. Dr. Jackson's research interests include economic analysis of diagnostic testing and physician utilization of laboratory tests. He is certified in clinical pathology by the American Board of Pathology.

Academic Office Locations

Academic Office Phone Number

Academic Office Address

(801) 583-2787 Ext 3191

ARUPARUP Laboratories500 Chipeta WaySalt Lake City, UT 84108

Academic Bio

Dr. Jackson received his BA in mathematics, his MS in medical informatics, and his MD from the University of Utah, and completed a clinical pathology residency at Dartmouth-Hitchcock Medical Center. Prior to his employment at ARUP, Dr. Jackson was a staff clinical pathologist and informaticist at Dartmouth-Hitchcock Medical Center, a product manager for a Belgium-based medical software firm, and a National Library of Medicine informatics fellow at the University of Utah.

Dr. Jackson’s research interests revolve around the application of diagnostic tests: their economic and clinical impact, comparison of actual utilization patterns to normative patterns, and ways to increase their value. His projects blend medical informatics with health services research.

One subset of his work involves traditional economic analysis (cost-effectiveness analysis, CEA) of diagnostic testing. Examples include the cost-effectiveness of blood safety measures, Helicobacter pylori diagnosis, and genetic testing in suspected neurofibromatosis. A major challenge in CEA of diagnostic tests is that their impact is indirect. Costs and benefits are driven primarily by the myriad and varying diagnostic and therapeutic actions by physicians in different settings; choice of a specific diagnostic test typically contributes a small portion of this variability. Idealized clinical processes may be attractive from the perspective of the modeler, but will often produce highly misleading results. Thus, the art of CEA in the diagnostic arena is largely a matter of framing assumptions in clinically realistic ways.

A second area of focus is measuring utilization rates of diagnostic tests and comparing them to idealized rates based on published guidelines. Examples include PSA screening for prostate cancer, workup of inherited thrombophilia, and HPV testing for cervical cancer screening. These research projects are closely aligned with an analytic program Dr. Jackson directs at ARUP, “Analyzing Test Ordering Patterns.” In this program, hospital and laboratory clients are provided with periodic feedback regarding tests that their physicians appear to be misordering or overordering. Data sets used for this analysis are quite broad but shallow. ARUP has data that crosses hundreds of different hospitals, which allows for cross-institutional comparison. On the other hand, the data is generally limited to test volumes, results, and patient age/sex. In the absence of the opportunity for clinical audit, these projects represent hypothesis generation as opposed to outcomes assessment. On the other hand, the majority of health services research in the U.S. is dependent on administrative data, esp. insurance claims data from public sources. In these data sets, diagnostic tests are represented by CPT codes which have a complex relationship to the underlying tests. For this reason, laboratory diagnostics are severely underrepresented in traditional health services research, and there is an important need for pragmatic observational studies based on data such as ARUP’s.

Dr. Jackson’s third area of research emphasis is promoting more effective and efficient use of diagnostic tests. Examples include modeling the value of bacterial strain typing for hospital infection control, estimation of the information content of test results, and measuring the impact of graphical laboratory reports and a pathology resident on-call program. These research projects are a direct outgrowth of his CMIO role at ARUP Laboratories.